James R. Wright

James R. Wright is an Associate Professor in the Department of Computing Science at the University of Alberta and a Fellow & Canada CIFAR AI Chair at the Alberta Machine Intelligence Institute (Amii). He holds a Ph.D. from the University of British Columbia (2016) under Kevin Leyton-Brown, with prior postdoctoral work at Microsoft Research (2016–2018). His research focuses on modeling human strategic behavior using machine learning, emphasizing interactions where participants' rewards depend on others' actions. Key areas include algorithm design for bounded rational agents, multiagent systems, and game theory applications.

Education: Ph.D. (Computer Science, UBC, 2016), M.Sc. (Computer Science, UBC, 2010), B.Sc. (Computing Science, Simon Fraser University, 2000).

Research interests include data-driven models for predicting human strategic decisions, algorithmic fairness, and reinforcement learning. Recent work addresses self-play guarantees in multiplayer games, peer prediction mechanisms, and software vulnerability detection via static analyzers. His work has been published in top venues like AAAI, NeurIPS, and ICML.

Awards include the ACM SIGecom Doctoral Dissertation Award (Honorable Mention), NSERC grants, and the Canada CIFAR AI Chair. He advises multiple graduate students and has served on numerous editorial and conference committees.

Teaching includes courses on artificial intelligence, modeling human strategic behavior, and intelligent systems. He leads the Algorithmic and Behavioral Game Theory (ABGT) reading group at UAlberta.